Das Projekt "Entwicklung eines Indikatorsystems für Degradationsstadien von Kesselmooren mit Hilfe von Laufkäfern und Spinnen" wird vom Umweltbundesamt gefördert und von Universität Berlin, Fachbereich Biologie, Chemie, Pharmazie, Institut für Biologie, Arbeitsgruppe Bodenzoologie und Ökologie durchgeführt. Due to mostly anthropogenic influence mires in Central Europe are undergoing rapid succession. We tried to indicate five degradation stages of a peculiar type of mires, so-called kettle-hole mires, which are located in the region of terminal moraines left by the pleistocene glaciation until 10,000 B.P. Using a database of more than 12,000 ground beetles belonging to more than 100 species sampled in 25 sites of various degradation, we tried to construct a bioindicatory system by the use of machine learning techniques. Model-tree induction yielded a classifier consisting of three decision-trees which was moderately successful in classifying mires into the correct degradation stage by using information about only nine species, thus breaking down the biotic information to a necessary minimum and creating an extremely parsimonious model. A translation of the decision-trees into fuzzy rule-based models increased bioindicatory efficiency: only one of ten unseen cases used for validation deviated more than one class from the correct degradation stage. At the moment, this model reflects a static picture of kettle-hole mire degradation, confirming what can be said upon macroscopic examination. Future studies must show whether also the more subtle dynamic aspects of mire degradation can be indicated by ground beetle occurrence.